Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17514/UKB-b-17514_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17514/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17514/UKB-b-17514_data.vcf.gz ...
Read summary statistics for 5071269 SNPs.
Dropped 1506 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1125082 SNPs remain.
After merging with regression SNP LD, 1125082 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0543 (0.0318)
Lambda GC: 1.0099
Mean Chi^2: 1.0088
Intercept: 0.9934 (0.0073)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:41:22 2019
Total time elapsed: 1.0m:3.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9085,
    "inflation_factor": 1,
    "mean_EFFECT": 6.5624e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 43452,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1125082,
    "ldsc_nsnp_merge_regression_ld": 1125082,
    "ldsc_observed_scale_h2_beta": 0.0543,
    "ldsc_observed_scale_h2_se": 0.0318,
    "ldsc_intercept_beta": 0.9934,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0099,
    "ldsc_mean_chisq": 1.0088,
    "ldsc_ratio": -0.75
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 5069774 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 5071269 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.671692e+00 5.766881e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.855583e+07 5.662391e+07 828.0000000 3.188750e+07 6.895179e+07 1.145553e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 6.600000e-06 8.039800e-03 -0.0630516 -5.091500e-03 1.540000e-05 5.109700e-03 6.476030e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.796900e-03 1.795500e-03 0.0057692 6.278200e-03 7.151300e-03 8.937300e-03 2.224190e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.979708e-01 2.892771e-01 0.0000003 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.979697e-01 2.892490e-01 0.0000003 2.469696e-01 4.970095e-01 7.483257e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.488120e-01 2.396401e-01 0.0630860 1.425510e-01 2.820860e-01 5.154290e-01 9.369120e-01 ▇▅▃▂▂
numeric AF_reference 43452 0.9914317 NA NA NA NA NA NA NA 3.425020e-01 2.360651e-01 0.0000000 1.477640e-01 2.847440e-01 5.049920e-01 1.000000e+00 ▇▆▃▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0015465 0.0107397 0.8900000 0.8855002 0.626208 0.7821490 NA
1 54676 rs2462492 C T 0.0076033 0.0105764 0.4700002 0.4722051 0.398605 NA NA
1 86028 rs114608975 T C -0.0121446 0.0170109 0.4799997 0.4752702 0.102878 0.0277556 NA
1 91536 rs6702460 G T 0.0121972 0.0104324 0.2399999 0.2423370 0.458206 0.4207270 NA
1 234313 rs8179466 C T -0.0461859 0.0201754 0.0219999 0.0220667 0.075032 NA NA
1 534192 rs6680723 C T -0.0127273 0.0118985 0.2800000 0.2847743 0.240339 NA NA
1 546697 rs12025928 A G 0.0183336 0.0147183 0.2099999 0.2128992 0.912974 NA NA
1 693731 rs12238997 A G -0.0083166 0.0099401 0.4000000 0.4027741 0.116669 0.1417730 NA
1 705882 rs72631875 G A -0.0123982 0.0143844 0.3900004 0.3887316 0.067676 0.0315495 NA
1 706368 rs55727773 A G -0.0058145 0.0073448 0.4299995 0.4285688 0.516340 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T 0.0083930 0.0089739 0.3500000 0.3496504 0.130762 0.1727240 NA
22 51216564 rs9616970 T C 0.0074378 0.0089325 0.4100001 0.4050321 0.131263 0.1563500 NA
22 51217954 rs9616974 G A 0.0058787 0.0113829 0.6100002 0.6055395 0.074187 0.0621006 NA
22 51218224 rs9616975 C A 0.0058717 0.0113875 0.6100002 0.6061157 0.074184 0.0619010 NA
22 51218377 rs2519461 G C 0.0049203 0.0113550 0.6600001 0.6647873 0.074767 0.0826677 NA
22 51219006 rs28729663 G A 0.0073746 0.0087466 0.4000000 0.3991550 0.141093 0.2052720 NA
22 51219387 rs9616832 T C 0.0049906 0.0114004 0.6600001 0.6615608 0.074514 0.0654952 NA
22 51221731 rs115055839 T C 0.0061891 0.0114101 0.5900000 0.5875296 0.074051 0.0625000 NA
22 51229805 rs9616985 T C 0.0079014 0.0114599 0.4899999 0.4905225 0.073878 0.0730831 NA
22 51237063 rs3896457 T C -0.0091415 0.0070730 0.2000000 0.1961976 0.295538 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.626208 ES:SE:LP:AF:ID  -0.00154652:0.0107397:0.05061:0.626208:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398605 ES:SE:LP:AF:ID  0.00760333:0.0105764:0.327902:0.398605:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.102878 ES:SE:LP:AF:ID  -0.0121446:0.0170109:0.318759:0.102878:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.458206 ES:SE:LP:AF:ID  0.0121972:0.0104324:0.619789:0.458206:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.075032 ES:SE:LP:AF:ID  -0.0461859:0.0201754:1.65758:0.075032:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240339 ES:SE:LP:AF:ID  -0.0127273:0.0118985:0.552842:0.240339:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912974 ES:SE:LP:AF:ID  0.0183336:0.0147183:0.677781:0.912974:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116669 ES:SE:LP:AF:ID  -0.00831662:0.00994006:0.39794:0.116669:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067676 ES:SE:LP:AF:ID  -0.0123982:0.0143844:0.408935:0.067676:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51634  ES:SE:LP:AF:ID  -0.0058145:0.00734485:0.366532:0.51634:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.099083 ES:SE:LP:AF:ID  0.0141808:0.0122063:0.60206:0.099083:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.841998 ES:SE:LP:AF:ID  0.00825147:0.0086051:0.468521:0.841998:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122306 ES:SE:LP:AF:ID  -0.00823867:0.00945612:0.420216:0.122306:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121538 ES:SE:LP:AF:ID  -0.00800501:0.00945596:0.39794:0.121538:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132349 ES:SE:LP:AF:ID  -0.00751637:0.00930109:0.376751:0.132349:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837739 ES:SE:LP:AF:ID  0.00632056:0.00831647:0.346787:0.837739:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837323 ES:SE:LP:AF:ID  0.00602203:0.00831265:0.327902:0.837323:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  0.00430163:0.00892182:0.200659:0.869049:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130497 ES:SE:LP:AF:ID  -0.00577734:0.00895548:0.283997:0.130497:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.868265 ES:SE:LP:AF:ID  0.00417963:0.00890851:0.19382:0.868265:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868375 ES:SE:LP:AF:ID  0.00440262:0.00891062:0.207608:0.868375:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868294 ES:SE:LP:AF:ID  0.00403747:0.00890843:0.187087:0.868294:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836914 ES:SE:LP:AF:ID  0.00560056:0.00828927:0.30103:0.836914:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.837606 ES:SE:LP:AF:ID  0.00554872:0.00831479:0.30103:0.837606:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838789 ES:SE:LP:AF:ID  0.00427203:0.00841938:0.21467:0.838789:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868645 ES:SE:LP:AF:ID  0.00421245:0.00889044:0.19382:0.868645:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  0.00416675:0.00886779:0.19382:0.868228:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866853 ES:SE:LP:AF:ID  0.00389608:0.00885826:0.180456:0.866853:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8683   ES:SE:LP:AF:ID  0.00398035:0.00887561:0.187087:0.8683:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868324 ES:SE:LP:AF:ID  0.00393047:0.00887587:0.180456:0.868324:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868329 ES:SE:LP:AF:ID  0.0039149:0.0088762:0.180456:0.868329:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868826 ES:SE:LP:AF:ID  0.00391268:0.0089002:0.180456:0.868826:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.837516 ES:SE:LP:AF:ID  0.00719108:0.00826771:0.420216:0.837516:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.837689 ES:SE:LP:AF:ID  0.00725722:0.00827343:0.420216:0.837689:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.86139  ES:SE:LP:AF:ID  0.00539693:0.0088529:0.267606:0.86139:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.708251 ES:SE:LP:AF:ID  0.00311408:0.00862853:0.142668:0.708251:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.104675 ES:SE:LP:AF:ID  -0.0060789:0.00994478:0.267606:0.104675:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.75951  ES:SE:LP:AF:ID  0.00718874:0.00699241:0.522879:0.75951:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.107463 ES:SE:LP:AF:ID  -0.0065913:0.00961633:0.309804:0.107463:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129795 ES:SE:LP:AF:ID  -0.00680015:0.00895032:0.346787:0.129795:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868319 ES:SE:LP:AF:ID  0.00473196:0.0088865:0.229148:0.868319:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130029 ES:SE:LP:AF:ID  -0.00699994:0.00894149:0.366532:0.130029:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868329 ES:SE:LP:AF:ID  0.00475348:0.00888619:0.229148:0.868329:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.266385 ES:SE:LP:AF:ID  0.00381883:0.00786108:0.200659:0.266385:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869718 ES:SE:LP:AF:ID  0.00462606:0.00891648:0.221849:0.869718:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096566 ES:SE:LP:AF:ID  -0.00598742:0.0102234:0.251812:0.096566:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128818 ES:SE:LP:AF:ID  -0.00677257:0.00896019:0.346787:0.128818:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129215 ES:SE:LP:AF:ID  -0.00634789:0.00894208:0.318759:0.129215:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868074 ES:SE:LP:AF:ID  0.0053235:0.00888968:0.259637:0.868074:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.100704 ES:SE:LP:AF:ID  -0.00564107:0.0101458:0.236572:0.100704:rs61768199